Research interests

In my lab we seek to understand how responses to ecological variation lead to divergence of populations across the landscape. We take on this challenge in a number of related ways. First, we use intensively managed species, both in nature and in captivity, to investigate the effects of anthropogenically-induced ecological changes on the evolutionary trajectory of populations. Second, we use data collected at broad scales and at high resolution to investigate the role of landscape heterogeneity in shaping spatial genetic structure at the earliest stages of divergence. Third, we use phylogeographic approaches to study evolution in highly mobile, continuously distributed species. We then apply our knowledge to the genetic management of wildlife populations, both in the wild and in captivity.

Evolutionary responses to intensive management

Populations are increasingly managed on restricted landscapes, and management practices such as anti-poaching efforts, culling, health care, and disease management are often undertaken at the scale of individual animals. In these populations, management decisions have important, yet largely unexplored, effects on genetic variation and population persistence. We explore the effects of wildlife management, and evaluate tools for managing populations, both in the wild and in captivity, that maximize long-term population persistence.  Some examples of ongoing projects in this area include:

  • We built an individual-based model, adaptable for any species but demonstrated using intensively managed bison herds, to show that strategies based on genome-wide measures of variation were best suited to preserving the evolutionary potential of wildlife populations (Giglio et al. 2016).  We have also found that it offers an improvement over currently employed strategies (Giglio et al. 2018).
  • Intensive management is a necessity in captive populations, often the last option for species persistence.  In collaboration with the San Diego Zoo, we are using genomic tools to develop an easily accessible workflow and infrastructure to improve genetic diversity retention for species with incomplete or poorly known pedigrees, to improve management of Species Survival Plan(R) species.
  • Translocations are a vital tool for wildlife management, and the success or failure of a translocated population has direct implications for genetic variation and population persistence. Our lab has documented a wide range of interactions between native and released individuals, including reduced dispersal from the release site, rapid expansion of released individuals into unoccupied habitat, and rampant hybridization (unidirectional or bidirectional, depending on the context). Much of this work has been done using the wild turkey as a model system (Mock et al. 2004, Latch and Rhodes 2005, Latch et al. 2006a and b), but I have also used river otters (Latch et al. 2008, Mowry et al. 2015), fishers (Hapeman et al. 2011), and tortoises (Latch et al. 2011, Mulder et al. 2017) to address questions surrounding translocation success.

Landscape genetics

In this broadly defined area of our research, we utilize a landscape genetics approach to understand how geographical and environmental features shape the patterns of spatial genetic structure we observe in nature. We have used a wide variety of study systems and novel analytical methods to investigate the evolutionary consequences of human landscape modifications (Latch and Rhodes 2005, Latch et al. 2011, Mowry et al. 2015), resource distribution and availability (Latch et al. 2008, Latch et al. 2011, Kierepka and Latch 2015), environmental contaminants (Latch et al. 2008), and recolonization dynamics (Latch et al. 2008, Latch et al. 2011, Hapeman et al. 2011). Through these projects, we have also improved statistical methodologies and rigorously evaluated their utility (Latch et al. 2006, Kierepka and Latch 2015, Anderson et al. 2015).

We are expanding our work in landscape genetics in two ways: 1) using genomic approaches to characterize the zone of introgression between mule deer and black-tailed deer, to provide more detailed insights into the mechanisms underlying hybridization in a non-model vertebrate, and 2) exploring the role of parasites and disease as an ecological factor influencing evolution and wildlife management.  We have recently begun projects on bats and prairie dogs that aim to employ landscape genetic approaches to understand disease ecology and host population persistence.

 

Phylogeography

Our work in phylogeography has largely focused on species with high mobility. High mobility and continuous distribution are expected to be genetically connected over broad spatial scales, and exhibit an overall lack of genetic structure. However, genetic structure can and does emerge in these widespread, highly mobile species (Latch et al. 2009, Hapeman et al. 2011, Latch et al. 2014, Kierepka and Latch 2016). We continue to expand on this work by adapting genomic technologies for non-model species, and applying them to wild populations (Powell et al. 2016). In particular, we are identifying and sampling genetic variation within coding genes scattered across the entire genome, to characterize variation in genes with known function.

 

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